Parameter Estimation in Enzyme-Kinetics with Consideration of Heteroscedasticity and Low Dose Data
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Date
1999
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Universitätsbibliothek Dortmund
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Abstract
In this paper we propose a simulation study in order to discuss four statistical models dealing with the problem of parameter estimation in enzyme-kinetics. The pseudo-maximum-likelihood estimators for the transform-both-sides-model and the weighted TBS-model are compared with least-square-estimators of the classical nonlinear regression model and the linearized Eadie-Hofstee-plot. Due to heteroscedasticity of enzyme-kinetic data in low dose experiments the proposed estimators are investigated.
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Keywords
heteroscedastic error variance, low dose data, Michaelis-Menten-kinetic, nonlinear regression model, pseudo-maximum-likelihood estimation, simulation study